Method for generating intra-particle morphological concentration/density maps and histograms of a chemically pure particulate substance

ABSTRACT

An method for generating intra-particle morphological concentration/density maps and histograms of a chemically pure particulate substance. Spectral imaging, in general, and focus-fusion multi-layer spectral imaging, in particular, combined with pattern recognition classification analysis are performed on individual particles for forming sets of single-particle spectral fingerprint data, characterized by single-particle spectral fingerprint spectra. Spectral shifts are identified in the single-particle spectral fingerprint data, for forming intra-particle region groups featuring sub-sets of intra-particle spectral fingerprint pattern data, each characterized by an intra-particle spectral fingerprint pattern spectrum. Each intra-particle region group is associated with different types of intra-particle morphological regions, where each region type is associated with a surface concentration value and a density value of the chemically pure substance in that imaged particle, for forming intra-particle morphological concentration/density data, which is used for generating an intra-particle morphological concentration/density map. A morphological concentration/density histogram, or frequency distribution, is generated from the intra-particle morphological concentration/density data, for illustrating global morphological distribution of concentration and density of the chemically pure substance throughout the entire multi-particle substance.

FIELD AND BACKGROUND OF THE INVENTION

[0001] The present invention relates to a method for determiningphysicochemical characteristics of a particulate substance and, moreparticularly, to a method for generating intra-particle morphologicalconcentration/density maps and histograms of a chemically pureparticulate substance by spectral imaging of individual particles of thechemically pure particulate substance and analyzing the spectral imagesusing pattern recognition classification analysis.

[0002] In the highly regulated biopharmaceutical industry, an importantstage during research and development of a new therapeutic product suchas a drug, high-performance chemical, or micro-organism, featuring atleast one chemically pure particulate substance either in the rawmaterial(s) and/or in the eventual finished product formulated as atablet, capsule, caplet, or loose powder, involves extensive and welldocumented laboratory analytical testing of the physicochemicalproperties and characteristics of each chemically pure particulatesubstance. Hereinafter, the term ‘chemically pure particulate substance’refers to particulate substance featuring one, or a combination ofseveral, chemically pure individual chemical compounds, where thechemically pure particulate substance is typically heterogeneous withrespect to physical location or morphological distribution of theconcentration and/or density of the at least one chemically purecompound throughout a given sized sample of the chemically pureparticulate substance.

[0003] Information about the physicochemical properties of eachchemically pure particulate substance are needed in a later stage forperforming pharmacodynamical studies, involving metabolic and efficacystudies of the therapeutic product when ingested by an animal or humanduring pre-clinical and clinical studies. Metabolic information aboutthe therapeutic product is needed for designing and evaluating efficacystudies, where the effectiveness of the therapeutic product forperforming the indicated therapeutic function in a subject is measured.Ultimately, information and data from the efficacy studies are used forestablishing the final formulation and recommended dosage levels of thenew therapeutic product, for dispensing to the consumer market.Correspondingly, data and information about the final formulation areused for establishing standardized quality control parameters andcriteria for full-scale manufacturing of the new therapeutic product.

[0004] Full-scale manufacturing of such a new or current, therapeuticproduct, involves extensive and well documented standardized qualitycontrol testing of each chemically pure particulate raw material and/orthe chemically pure particulate finished product, according toestablished quality control and quality assurance parameters andcriteria. Similar to the research and development stages of such aproduct, this involves laboratory analytical testing and classificationof the physicochemical properties and characteristics of each chemicallypure particulate substance relating to the therapeutic product.

[0005] Laboratory analytical testing of such a particulate substance,during research and development stages or during routine finishedproduct quality control testing, typically includes measuring anddetermining concentration(s) and/or density(ies), and morphologicalproperties and characteristics such as particle size and particlegeometry, shape, or porosity distributions of a sample of the chemicallypure particulate substance, in a statistically meaningful manner.Typically, such laboratory testing also includes measuring anddetermining dissolution properties of each applicable or selectedchemically pure particulate substance. Dissolution testing provides dataand information about the kinetics and thermodynamics of dissolution ofa given chemically pure particulate substance in a variety of solvents.As indicated above, such detailed information about the physicochemicalproperties of each chemically pure particulate substance is valuable andused for either understanding, classifying, or quality control testingpharmacodynamical behavior of the therapeutic product.

[0006] It is commonly known in the field of physical chemistry ofparticulate matter that dissolution properties and behavior of aparticle, and therefore, of a sample of particulate substance featuringa plurality of particles, in a liquid medium, either in-vitro orin-vivo, are closely related to and functions of morphologicalproperties and characteristics such as particle size, geometry or shape,and porosity distributions, and, concentration and/or density, of theparticulate substance. Thus, measuring and determining data andinformation about the latter particle properties and characteristics,are useful for highly accurately and reproducibly determining,understanding, classifying, and testing dissolution properties andbehavior of the particulate substance. This relationship is clearlyapplicable to laboratory analytical testing of chemically pureparticulate substances extensively performed by the biopharmaceuticalindustry, as described above.

[0007] There are extensive prior art methods, devices, and systems,relating to accurately and reproducibly measuring and determiningmorphological properties and characteristics of a particulate substance,where these are typically based on imaging the particulate substance.Spectral imaging is currently a widely used technique for imagingparticles. In spectral imaging, a particulate substance is affected in away, for example, excitation by incident ultraviolet light upon thesubstance, which causes the substance to emit light featuring anemission spectra. Emitted light is recorded by an instrument such as ascanning interferometer that generates a set of interferogram images,which in turn are used to produce a spectral image, also referred to asa cube image, of the substance. Each cube (spectral) image is a threedimensional data set of voxels (volume of pixels) in which twodimensions are spatial coordinates or position, (x, y), in the substanceand the third dimension is the wavelength, (λ), of the imaged (emitted)light of the substance, such that coordinates of each voxel in aspectral image or cube image may be represented as (x, y, λ). Anyparticular wavelength, (λ), of imaged light of the substance isassociated with a set of cube images or spectral fingerprints of thesubstance in two dimensions, for example, along the x and y directions,whereby voxels having that value of wavelength constitute the pixels ofa monochromatic image of the substance at that wavelength. Each cubeimage, featuring a range of wavelengths of imaged light of the substanceis analyzed to produce a two dimensional map of the chemicalcomposition, or of some other physicochemical property of the substance,for example, particle size distribution.

[0008] An example of a method and system for real-time, on-line chemicalanalysis of particulate substances, for example, polycyclic aromatichydrocarbon (PAH) particles in aerosols, in which the PAH substance isexcited to emit light, for example fluorescence, is that of U.S. Pat.No. 5,880,830, issued to Schechter, and manufactured by Green VisionSystems Ltd. of Tel Aviv, Israel, the teachings of which areincorporated by reference for all purposes as if fully set forth herein.In the disclosed method, spectral imaging techniques are implemented toacquire an image and analyze the properties of fixed position PAHparticles. As part of this method, air is sampled by means of a highvolume pump sucking a large volume of air featuring aerosol contaminatedwith PAH particles onto a substrate, followed by on-line imaging andscene analysis of the stationary particles.

[0009] A method of calibration and real-time analysis of particles isdescribed in U.S. Pat. No. 6,091,843, to Moshe et al., the teachings ofwhich are incorporated by reference for all purposes as if fully setforth herein. The method described, is based on using essentially thesame system of U.S. Pat. No. 5,880,830, for acquiring spectral images ofstatic particles on a filter. In brief, there is disclosed a method ofanalyzing particles for the presence of chemical or biological species,by spectral imaging of the particles. The output of the imageacquisition is, for each imaged portion of a two-dimensional surfacehost to the particles, a set of images, each image at a differentwavelength. These images are digitized and analyzed by standard imageprocessing methods to produce, for each imaged portion of thetwo-dimensional surface, spectral images of targets.

[0010] In the disclosure of U.S. Pat. No. 6,091,843, targets areidentified in static particle images and are classified according tomorphology type and spectrum type. Each target is assigned a value of anextensive property. A descriptor vector is formed, where each element ofthe descriptor vector is the sum of the extensive property values forone target class. The descriptor vector is transformed, for example, toa vector of mass concentrations of chemical species of interest, or ofnumber concentrations of biological species of interest, using arelationship determined in the calibration procedure. In the calibrationprocedure, spectral images of calibration samples of static particleshaving known composition are acquired, and empirical morphology typesand spectrum types are inferred from the spectral images. Targets areidentified in the calibration spectral images, classified according tomorphology type and spectrum type, and assigned values of an extensiveproperty. For each calibration sample, a calibration descriptor vectorand a calibration concentration vector is formed. A collectiverelationship between the calibration descriptor vectors and thecalibration concentration vectors is found using chemometric methods.

[0011] In conventional scene analysis using the above described methodsand systems for spectral imaging of individual particles, for example,for each scene, there is auto-focusing, where a best focal position isdetermined for use in analyzing or classifying particle properties. Forsome scenes, this is possible, and a focused image may be obtained in anautomatic manner. Typically, an auto-focus module is coupled with acomputer controlled mechanism that automatically changes the focalposition, by moving along an axis parallel to the optical axis of theimaging or focusing sensor, thereby enabling identification of a goodfocal position. For other scenes, a good focal position is notguaranteed to exist and further image processing based on focus-fusionmethodology is required.

[0012] When focused images of spatially varying or depth dependentscenes can not be generated by using such auto-focus electromechanicalmeans, such that single focal positions can not be identified, focusedrepresentations of the scenes can be constructed by combining or fusingselected portions of several defocused images of each scene. Thisprocess is referred to as focus-fusion imaging, and the resulting imagesof such processing are referred to as a focus-fusion images. Defocusedimages, for example, those acquired during auto-focusing, are fusedtogether such that each target in a given scene is in correct focus.Scene targets are detected by analyzing either focused images, if theyexist, or focus-fusion images.

[0013] Spectral imaging of spatially varying, depth dependent, ormulti-layered samples of particles is not described in the abovereferenced methods and systems. Imaging and image analysis of a randomsingle two-dimensional layer of a particulate substance are ordinarilystraightforward. However, multi-layer imaging and image analysis ofdepth dependent particulate substances, for example, multi-layered dryparticles, or particles in a frozen or immobilized suspension, aresubstantially more complex. Nevertheless, there are instances where itis necessary to obtain property and classification information of depthdependent particulate substances, in-situ, for example, as part ofsampling an industrial process. More often than not, images obtained ofsuch particulate substances are defocused, and require special imageprocessing techniques, such as focus-fusion, for obtaining usefulinformation about the substances.

[0014] Additionally, the above described disclosures feature usefulmethods and systems for acquiring and analyzing spectral images ofparticles, but are limited to identifying and quantifying the presenceof species on particles, where the species are typically consideredparticle impurities, and therefore, there is no description of spectralimaging and analysis of a chemically pure particulate substance.Furthermore, there is no description of a method for applying thedescribed pattern recognition classification procedures for analyzingintra-particle spectral images of individual particles, where theconcentration and/or density of the chemical substance in the hostparticles, separate from impurity species concentration, are spectrallyrelated to particle morphological characteristics such as particle sizeand/or shape.

[0015] Recently, it has been disclosed that scene analysis by applyingfocus-fusion methodology to defocused images acquired by multi-layerspectral imaging of depth dependent particulate substances is quiteuseful for detecting and classifying in-situ physicochemical informationof the particles, such as particle size distribution, morphologicalfeatures, including structure, form, and shape characteristics, andchemical composition, which ideally involve multi-layerthree-dimensional image analysis. In U.S. patent application Ser. No.09/727,753, filed Dec. 4, 2000, entitled “Method For In-situFocus-fusion Multi-layer Spectral Imaging And Analysis Of ParticulateSamples”, which is a Continuation-in-Part of U.S. patent applicationSer. No. 09/322,975, filed Jun. 1, 1999, of same title, which is aContinuation-in-Part of U.S. patent application Ser. No. 09/146,361 (nowU.S. Pat. No. 6,091,843, previously summarized above), the teachings ofwhich are incorporated by reference for all purposes as if fully setforth herein, there is disclosed a method for in-situ focus-fusionmulti-layer spectral imaging and analysis of depth dependent particulatesubstances.

[0016] In U.S. patent application Ser. No. 09/727,753, a unique methodof focus-fusion is applied to focused and defocused images acquired frommulti-layer spectral imaging of a depth dependent particulate substance,in order to construct focused fused cube (spectral) imagerepresentations of the imaged particles, thereby generating a focusedimage of essentially each particle in a sample of the substance. Thedisclosed method features the use of a uniquely defined and calculatedfocus-fusion factor parameter, F_(b), which combines (1) empiricallydetermined particle physicochemical information and parameters relatingto (i) particle chemical composition and associated chemistry, andrelating to (ii) particle morphology such as particle size and shape,with (2) empirically determined particle spectral information andparameters such as (i) pixel intensity, (ii) signal-to-noise ratio(S/N), (iii) image sharpness, (iv) spectral distances, and (v) spectralfingerprints relating to spectral emission patterns of individualparticles. The focus-fusion factor parameter, F_(b), is used in criticalsteps of image detection, image analysis, and in algorithms forclassification of particle characteristics. This uniquely determinedparameter enables achievement of high levels of accuracy and precisionin detection and classification of the substance, in general, and of theindividual particles, in particular.

[0017] The disclosed method includes collecting and analyzingphysicochemical and multi-layer spectral data relating to the particlesin the sample, including mapping of three-dimensional positions ofparticles, particle sizes, and characteristics of particle emissionspectra. Scene information, in the form of spectral fingerprints, usedin the analysis of focus-fusion of the multi-layer spectral images isfurther processed in order to generate relevant in-situ physicochemicalinformation of the particles, such as particle size distribution,morphological features, including structure, form, and shapecharacteristics, and chemical composition. The focus-fusion multi-layerspectral image analysis includes a sophisticated classificationprocedure for extracting, on-line, useful information relating toparticle properties and characteristics needed for generating a reportapplicable to monitoring or controlling an industrial process.

[0018] According to that disclosure, the method of focus-fusionmulti-layer spectral imaging and analysis of depth dependent particulatesamples can be applied to a sample of chemically pure particles.However, each described alternative procedure for analyzing the data ofthe fused cube images of the particles, is with respect to either anindividual particle as the simplest unit or object of imaging andanalysis, or with respect to a sample of many such particles. There isno description with respect to variation of intra-particle properties orcharacteristics, and consequently, there is no relating variation ofintra-particle properties or characteristics such as intra-particleconcentration and/or density to intra-particle focus-fusion spectralimage data.

[0019] In actuality, it turns out, especially with regard to laboratoryanalytical testing of particulate materials, as currently practiced bypharmaceutical, biotechnology, and chemical industries, that at a moredetailed level, measuring and determining physicochemical properties andcharacteristics of a sample of particulate substance, such as of achemically pure particulate substance, at the particle level, areinsufficient for highly accurately and reproducibly relating thephysicochemical data and information to results of pharmacodynamicalstudies of the particulate substance. This phenomenon is particularlyevident where a chemically pure particulate substance is heterogeneouswith respect to intra-particle and/or inter-particle morphologicaldistribution of the concentration and/or density of at least onechemically pure compound throughout the chemically pure particulatesubstance.

[0020] There is thus a need for, and it would be highly advantageous tohave a method for generating intra-particle morphologicalconcentration/density maps and histograms of a chemically pureparticulate substance by spectral imaging, in general, and, byfocus-fusion multi-layer spectral imaging, in particular, of individualparticles of the chemically pure particulate substance and analyzing thespectral images using pattern recognition classification analysis.

SUMMARY OF THE INVENTION

[0021] The present invention relates to a method for generatingintra-particle morphological concentration/density maps and histogramsof a chemically pure particulate substance by spectral imaging, ingeneral, and, by focus-fusion multi-layer spectral imaging, inparticular, of individual particles of the chemically pure particulatesubstance and analyzing the spectral images using pattern recognitionclassification analysis.

[0022] Thus, according to the present invention, there is provided amethod for generating intra-particle morphological concentration/densitymaps and histograms of a chemically pure particulate substance,comprising the steps of: (a) acquiring a set of spectral images by aspectral imaging system for each of a number of particles of thechemically pure particulate substance having a plurality of theparticles; (b) performing pattern recognition classification analysis oneach set of the acquired spectral images for each imaged particle, forforming a number of sets of single-particle spectral fingerprint data;(c) identifying at least one spectral shift in each set ofsingle-particle spectral fingerprint data associated with each imagedparticle, for forming an intra-particle region group featuring aplurality of sub-sets of intra-particle spectral fingerprint patterndata, where selected data elements in each sub-set are shifted relativeto corresponding data elements in each remaining sub-set in the sameintra-particle region group; (d) forming a set of intra-particlemorphological concentration/density data relating to each imagedparticle from each intra-particle region group; (e) generating each ofthe intra-particle morphological concentration/density maps from eachset of the intra-particle morphological concentration/density data; and(f) generating each of the morphological concentration/densityhistograms from a plurality of the sets of the intra-particlemorphological concentration/density data, for illustrating astatistically based global morphological distribution of surfaceconcentration and density throughout the chemically pure particulatesubstance.

[0023] According to another aspect of the present invention, there isprovided a method for identifying intra-particle morphologicaldistribution of surface concentration and density of a chemically pureparticulate substance, comprising the steps of: (a) acquiring a set ofspectral images by a spectral imaging system for each of a number ofparticles of the chemically pure particulate substance having aplurality of the particles; (b) performing pattern recognitionclassification analysis on each set of the acquired spectral images foreach imaged particle, for forming a number of sets of single-particlespectral fingerprint data; (c) identifying at least one spectral shiftin each set of single-particle spectral fingerprint data associated witheach imaged particle, for forming an intra-particle region groupfeaturing a plurality of sub-sets of intra-particle spectral fingerprintpattern data, where selected data elements in each sub-set are shiftedrelative to corresponding the data elements in each remaining sub-set inthe same intra-particle region group; (d) forming a set ofintra-particle morphological concentration/density data relating to eachimaged particle from each intra-particle region group; and (e) forming aplurality of intra-particle morphological region types from each set ofthe intra-particle morphological concentration/density data, where eachintra-particle morphological region type is associated with a differentvalue of the surface concentration and a different value of the densityof the chemically pure particulate substance, thereby identifying theintra-particle morphological distribution of the surface concentrationand density of the chemically pure particulate substance.

[0024] In the method of the present invention, spectral imaging, ingeneral, and focus-fusion multi-layer spectral imaging, in particular,combined with appropriate pattern recognition classification analysisare performed on a number of individual particles of a plurality ofparticles of the chemically pure particulate substance, for forming aplurality of sets of single-particle spectral fingerprint data, whereeach set is characterized by a single-particle spectral fingerprintspectrum. This information is stored in a single-particle scenariodatabase.

[0025] In each set of single-particle spectral fingerprint data,spectral shifts are identified, for forming an intra-particle regiongroup featuring a plurality of sub-sets of intra-particle spectralfingerprint pattern data. Each sub-set is characterized by anintra-particle spectral fingerprint pattern spectrum, which isassociated with the same single-particle spectral fingerprint spectrumas the other intra-particle spectral fingerprint pattern spectra of theother sub-sets in the same intra-particle region group. This informationis stored in an intra-particle scenario database.

[0026] Each intra-particle region group featuring the plurality ofsub-sets of intra-particle spectral fingerprint pattern data isassociated with a plurality of intra-particle morphological region typeidentifiers, where each intra-particle morphological region typeidentifier is associated with a surface concentration value and adensity value of the chemically pure substance in that imaged particle,for forming a set of intra-particle morphological concentration/densitydata, stored in an intra-particle morphological concentration/densitydatabase.

[0027] For each particle, the set of intra-particle morphologicalconcentration/density data is used for generating an intra-particlemorphological concentration/density map for illustrating local,intra-particle, morphological distribution of surface concentration anddensity of the chemically pure substance throughout the imaged particle.For that number of imaged and analyzed particles of the plurality ofparticles of the particulate substance, a morphologicalconcentration/density histogram, or frequency distribution, is generatedfrom a plurality of sets of the intra-particle morphologicalconcentration/density data, for illustrating a statistically basedglobal morphological distribution of concentration and densitythroughout the entire chemically pure particulate substance.

[0028] The method and system of the present invention, compared tocurrently used methods and systems, provide new capabilities foreffectively and efficiently determining and classifying intra-particlemorphological concentration/density data and related information, forapplication to the pharmaceutical, biotechnology, chemical, and otherindustries requiring intra-particle physicochemical analysis andcharacterization of a chemically pure particulate substance.

[0029] The method of the present invention is generally applicable tospectral imaging of chemically pure particulate substances, and, isparticularly applicable to multi-layer focus-fusion spectral imaging,multi-layer scene analysis, and multi-layer physicochemicalcharacterization of chemically pure particulate substances featuringdepth dependency, where layer or depth variations of imaged samples ofpowders, frozen suspensions of powders, biological specimens, or othermulti-layered chemically pure particulate samples are typically largecompared to differential imaging distances, and where there is a needfor effectively and efficiently determining and classifyingintra-particle morphological concentration/density data and relatedinformation of the chemically pure particulate substance. The presentinvention is especially well suited for analyzing spectral images ofchemically pure particulate substances of medicines, for example,medicines containing both chemically pure active ingredients andchemically pure inactive ingredients, whereby there is distinguishingand characterizing physicochemical properties and features of the activeand inactive ingredients.

BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The invention is herein described, by way of example only, withreference to the accompanying drawings, wherein:

[0031]FIG. 1 is an illustration of spectral imaging, in general, and,focus-fusion multi-layer spectral imaging, in particular, of achemically pure particulate substance featuring intra-particleheterogeneous morphology and regions of varying concentration/density,in accordance with the present invention;

[0032]FIG. 2 is a schematic diagram illustrating the step of identifyingspectral shifts in intra-particle spectral imaging data, in general,and, focus-fusion multi-layer spectral imaging data, in particular, inaccordance with the present invention;

[0033]FIG. 3 is a schematic diagram illustrating an intra-particlemorphological concentration/density map of a particle, generated fromthe exemplary set of intra-particle morphological concentration/densitydata formed from the results of FIG. 2, in accordance with the presentinvention; and

[0034]FIG. 4 is a schematic diagram illustrating a morphologicalconcentration/density histogram generated from a plurality of sets ofintra-particle morphological concentration/density map data,corresponding to a statistically based global morphological distributionof concentration of the chemically pure substance throughout the entiremulti-particle sample, in accordance with the present invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0035] The present invention relates to a method for determiningphysicochemical characteristics of a particulate substance and, moreparticularly, to a method for generating intra-particle morphologicalconcentration/density maps and histograms of a chemically pureparticulate substance by spectral imaging, in general, and, byfocus-fusion multi-layer spectral imaging, in particular, of individualparticles of the chemically pure particulate substance and analyzing thespectral images using pattern recognition classification analysis.

[0036] As previously indicated above, the term ‘chemically pureparticulate substance’ refers to particulate substance featuring atleast one, or a combination of several, chemically pure individualchemical compounds, where the chemically pure particulate substance istypically heterogeneous with respect to physical location ormorphological distribution of the concentration and/or density of the atleast one chemically pure compound throughout a given sized sample ofthe chemically pure particulate substance. Exemplary types of achemically pure particulate substance are a powder, a powder mixture, amedicinal powder featuring at least one active ingredient and at leastone inactive ingredient, a frozen suspension of a powder, and abiological specimen. According to the actual type of chemically pureparticulate substance subjected to the spectral imaging, physicochemicalproperties and characteristics of the particles of the chemically pureparticulate substance are either independent or dependent upon layer ordepth into each particle.

[0037] It is to be understood that the invention is not limited in itsapplication to the details of the order or sequence of steps ofoperation or implementation, or, construction, arrangement, andcomposition of the components of exemplary analytical instrumentationand related equipment, set forth in the following description, drawings,or examples. The invention is capable of other embodiments or of beingpracticed or carried out in various ways. Also, it is to be understoodthat the phraseology and terminology employed herein are for the purposeof description and should not be regarded as limiting.

[0038] Steps, sub-steps, components, operation, and implementation ofthe method for generating intra-particle morphologicalconcentration/density maps and histograms of a chemically pureparticulate substance by spectral imaging, in general, and, byfocus-fusion multi-layer spectral imaging, in particular, of individualparticles of the chemically pure particulate substance and analyzing thespectral images using pattern recognition classification analysis,according to the present invention are better understood with referenceto the following description and the accompanying drawings.

[0039] While searching for a method of applying spectral imaging, ingeneral, and, focus-fusion multi-layer spectral imaging (focusing on asingle particle layer or a multiple of particle layers, where each layercorresponds to one spectral image cube per field-of-view of a spectralimaging device), in particular, combined with pattern recognitionclassification analysis for improving physicochemical characterizationof a sample of a chemically pure, but morphologically heterogeneous,particulate substance, it was unexpectedly determined at the singleparticle level, that each spectrum, in each group of spectra associatedwith a set of imaged targets, or ‘Blobs’ (the terms ‘targets’ and‘Blobs’ are defined and described in detail in previously cited U.S.patent application Ser. No. 09/727,753, above), within the same particleand assigned the same spectral fingerprint of that particle, featuresspectral parameters, for example, emission wavelength and/or emissionintensity or amplitude, shifted with respect to the corresponding samespectral parameters of each of the remaining spectra of that same groupof spectra. Accordingly, each spectrum in each such group of spectracorresponds to a different particular pattern of the same spectralfingerprint assigned to that group of spectra, associated with an imagedparticle. Hereinafter, a pattern of a spectral fingerprint associatedwith a set of spectra is referred to as a ‘spectral fingerprintpattern’. Thus, each group of spectra associated with a characteristicspectral fingerprint of the particle features a plurality ofintra-particle spectral fingerprint patterns of the imaged particle.

[0040] Based on this newly determined sub-classification of the spectralimaging data, in general, and of the focus-fusion multi-layer spectralimaging data, in particular, it is possible to associate differentspectral fingerprint patterns of the same particle with differentintra-particle morphological regions varying in concentration and/ordensity of the chemically pure, but morphologically heterogeneous,particulate substance. Furthermore, it was determined by the inventorsthat shifts in spectral parameters, herein, also referred to as spectralshifts, present in a given group of intra-particle spectral fingerprintpatterns of an individual particle are primarily due to local,intra-particle, variation or heterogeneity in particle morphology suchas shape or geometry, and porosity, and, due to local, intra-particle,variation or heterogeneity in surface concentration and/or density ofthe chemically pure substance.

[0041] The novelty of the present invention is based on identifyingshifts in spectral parameters, for example, emission wavelength and/oremission intensity or amplitude, present in classified spectral imagingspectral fingerprint data, in general, and on identifying shifts inspectral parameters in classified focus-fusion multi-layer spectralimaging spectral fingerprint data, in particular, and using theidentified spectral shift data for revealing, correlating, anddisplaying intra-particle morphological and concentration/density datain the forms of intra-particle morphological concentration/density mapsand histograms of the chemically pure particulate substance, which arerepresentative of, and directly applicable to, intra-particlephysicochemical analysis and characterization of a chemically pureparticulate substance.

[0042] In Step 1 of the method for generating intra-particlemorphological concentration/density maps and histograms of a chemicallypure particulate substance, there is acquiring a set of spectral images,in general, and acquiring a set of focus-fusion multi-layer spectralimages of one or more particle layers, in particular, by a spectralimaging system, for each of a number of particles of the chemically pureparticulate substance having a plurality of particles.

[0043] In Step 2, there is performing pattern recognition classificationanalysis on the set of the acquired spectral images, in general, and, onthe set of the acquired focus-fusion multi-layer spectral images, inparticular, for each of the number of imaged particles of the chemicallypure particulate substance, for forming at least the same number of setsof single-particle spectral fingerprint data, where each set ofsingle-particle spectral fingerprint data is associated with a singleparticle. The plurality of sets of the single-particle spectralfingerprint data is stored in a single-particle scenario database.

[0044] Steps 1 and 2 are performed according to the previouslysummarized prior art disclosures of U.S. patent application Ser. No.09/322,975, U.S. patent application Ser. No. 09/146,361, U.S. Pat. No.6,091,843, and U.S. Pat. No. 5,880,830, the teachings of each of whichare incorporated by reference for all purposes as if fully set forthherein. For particularly understanding the present invention, thefollowing description, referring to FIG. 1, based on the abovereferenced disclosures, is herein provided.

[0045] Referring now to FIG. 1, an illustration of spectral imaging, ingeneral, and, focus-fusion multi-layer spectral imaging, in particular,of a chemically pure particulate substance featuring intra-particleheterogeneous morphology and regions of varying concentration/density,chemically pure particulate substance 10, featuring a plurality of Nindividual particles, is positioned in an imaging sample holding device12, part of spectral imaging system 14, where spectral imaging system 14is operative for detecting, acquiring, measuring, processing, anddisplaying spectral imaging data and information, in general, andfocus-fusion multi-layer spectral imaging data and information, inparticular. Imaging source energy 16, preferably, but not limited to,electromagnetic radiation, supplied by imaging energy source 18, isincident upon substance 10, and is affected by any combination ofabsorption, reflection, transmission, diffraction, and/or scattering,mechanisms, by each imaged particle, p_(i), for a number, n, of imagedparticles, for i=1 to n, where n is less than or equal to N. Spectralimaging system 14 collects affected energy 20 by energy collector 22.

[0046] In substance 10, for each imaged particle, p_(i), for example,p₁, p₂, and p₃, a set of spectral images, in general, and, a set offocus-fusion multi-layer spectral images, in particular, is acquired.Pattern recognition classification analysis is performed on each set ofthe acquired spectral images, in general, and, on each set of thefocus-fusion multi-layer spectral images, in particular, for each imagedparticle, p_(i), of a number of imaged particles, for example, p₁, p₂,and p₃, for forming an equal number of sets of single-particle spectralfingerprint data, F(p_(i)), for example, F(p₁), F(p₂), and F(p₃),respectively, where each set of single-particle spectral fingerprintdata is associated with a single imaged particle.

[0047] Each set of single-particle spectral fingerprint data, F(p_(i)),is characterized by a single-particle spectral fingerprint spectrum,S(p_(i)), featuring intensity or amplitude, A(p_(i)), plotted as afunction of affected energy, E(p_(i)), 20 collected during imagingparticle, p_(i), by spectral imaging system 14. Preferably, affectedenergy, E(p_(i)), 20 is expressed in terms of wavelength, frequency, orwavenumber, of electromagnetic radiation, such as fluorescent orphosphorescent light, emitted by an imaged particle, p_(i). This data isstored in a single-particle scenario database. This process is clearlyillustrated in FIG. 1, where each set of single-particle spectralfingerprint data, F(p₁), F(p₂), and F(p₃), for each imaged particle p₁,p₂, and p₃, respectively, is characterized by a single-particle spectralfingerprint spectrum, S(p₁), S(p₂), and S(p₃), respectively, referencedby 30, 32, and 34, respectively.

[0048] In Step 3, there is identifying at least one spectral shift,preferably, a plurality of spectral shifts, in each set of thesingle-particle spectral fingerprint data associated with a singleparticle, for forming an intra-particle region group featuring aplurality of sub-sets of intra-particle spectral fingerprint patterndata, where selected data elements in each sub-set are shifted relativeto corresponding data elements in each remaining sub-set in the sameintra-particle region group. This step represents the main, but notonly, aspect of the novelty of the present invention.

[0049] This spectral shift identification step is performed for each ofthe number, n, imaged particles of the substance, for forming aplurality of intra-particle region groups of sub-sets of intra-particlespectral fingerprint pattern data, relating to the entire chemicallypure particulate substance 10. This data is stored in an intra-particlescenario database.

[0050] In general, the identification procedure involves analyzing theplurality of spectral images for those particular spectral images whichonly slightly differ by relatively small shifts in the affected energy,E(p_(i)), and/or, only slightly differ by relatively small shifts in theintensity or amplitude, A(p_(i)), collected by spectral imaging system14. Preferably, the identification procedure involves analyzing theplurality of spectral images for those particular spectral images whichonly slightly differ by relatively small shifts in the affected energy,E(p_(i)), 20, in terms of a shift in wavelength, frequency, or,wavenumber, of fluorescent or phosphorescent light emitted by an imagedparticle, p_(i), and collected by spectral imaging system 14.

[0051] Specifically, there is identifying at least one spectral shift,s_(i), in each set of single-particle spectral fingerprint data,F(p_(i)), associated with an imaged particle, p_(i), for forming anintra-particle region group, RG(p_(i)), featuring a plurality ofsub-sets of intra-particle spectral fingerprint pattern data, FP(p_(i),R_(j)), where selected data elements, for example, affected energy,E(p_(i)), and/or, intensity or amplitude, A(p_(i)), in each sub-set,FP(p_(i), R_(j)), are shifted relative to corresponding data elements ineach remaining sub-set, FP(p_(i), R_(k)), for k not equal to j, in thesame intra-particle region group, RG(p_(i)).

[0052] Intra-particle region group sub-set identifier, R_(j), for j=1 toJ different sub-sets in each intra-particle region group, is used fordistinguishing among the plurality of sub-sets of intra-particlespectral fingerprint pattern data, FP(p_(i), R_(j)), associated with thesame set of single-particle spectral fingerprint data, F(p_(i)). Thisclassification enables performing Step 4 of forming a set ofintra-particle morphological concentration/density data from eachintra-particle region group, RG(p_(i)), featuring the plurality ofsub-sets of intra-particle spectral fingerprint pattern data, FP(p₁,R_(j)).

[0053] Each sub-set of intra-particle spectral fingerprint pattern data,FP(p_(i), R_(j)), is characterized by an intra-particle spectralfingerprint pattern spectrum, S(p_(i), R_(j)), featuring intensity oramplitude, A(p_(i), R_(j)), plotted as a function of affected energy,E(p_(i), R_(j)), 20 collected during imaging particle, p_(i), byspectral imaging system 14. This data is stored in an intra-particlescenario database.

[0054] The above described process of identifying spectral shifts isclearly illustrated in FIG. 2, a schematic diagram illustrating the stepof identifying spectral shifts in intra-particle spectral imaging data,in general, and, focus-fusion multi-layer spectral imaging data, inparticular. For example, in the set of single-particle spectralfingerprint data, F(p₁), 30 (from FIG. 1) associated with imagedparticle, p₁, and characterized by single-particle spectral fingerprintspectrum, S(p₁), there is identifying at least one spectral shift,s_(i), of selected data elements, for example, affected energy,E(p_(i)), and/or, intensity or amplitude, A(p_(i)), where potentiallyidentified spectral shifts, s_(i), are referenced in FIG. 2 by the fourdirectional crossed arrows 36, for forming intra-particle region group,RG(p₁) 38. In this example, for imaged particle p₁, RG(p₁) 38 featuresfour sub-sets of intra-particle spectral fingerprint pattern data,FP(p₁, R₁), FP(p₁, R₂), FP(p₁, R₃), and FP(p₁, R₄), where each sub-setis characterized by a corresponding intra-particle spectral fingerprintpattern spectrum, S(p₁, R₁), S(p₁, R₂), S(p₁, R₃), and S(p₁, R₄),respectively, referenced by 30A, 30B, 30C, and 30D, respectively.

[0055] In FIG. 2, three spectral shifts, s₁, s₂, and, s₃, are shownidentified, whereby selected data elements, for example, E(p₁, R_(j)),in each sub-set, FP(p₁, R_(j)), are shifted relative to correspondingdata elements, E(p₁, R_(k)), in each remaining sub-set, FP(p₁, R_(k)),for k not equal to j, in the same intra-particle region group, RG(p₁)36. In this particular example, the first sub-set of intra-particlespectral fingerprint pattern data, FP(p₁, R₁), characterized by thecorresponding intra-particle spectral fingerprint pattern spectrum,S(p₁, R₁), referenced by 30A, is shown as a baseline used in identifyingand illustrating the three spectral shifts, s₁, s₂, and, s₃, of selecteddata elements, in this case, E(p₁, R₁), from corresponding dataelements, in this case, E(p₁, R₂), E(p₁, R₃), and E(p₁, R₄),respectively, in the three remaining sub-sets of intra-particle spectralfingerprint pattern data, FP(p₁, R₂), FP(p₁, R₃), and FP(p₁, R₄),respectively, where each remaining sub-set is characterized by thecorresponding intra-particle spectral fingerprint pattern spectrum,S(p₁, R₂), S(p₁, R₃), and S(p₁, R₄), respectively, referenced by 30B,30C, and 30D, respectively.

[0056] In Step 4, there is forming a set of intra-particle morphologicalconcentration/density data, relating to each imaged particle of thechemically pure particulate substance, from each intra-particle regiongroup featuring the plurality of sub-sets of intra-particle spectralfingerprint pattern data associated with a corresponding set ofsingle-particle spectral fingerprint data.

[0057] For each imaged particle, the set of intra-particle morphologicalconcentration/density data features a plurality of intra-particlemorphological region types, where each intra-particle morphologicalregion type is associated with a surface concentration value and adensity value of the chemically pure substance. This step is performedfor each of the number, n, imaged particles of the substance, forforming a plurality of sets of intra-particle morphologicalconcentration/density data, relating to the entire chemically pureparticulate substance 10. This data is stored in an intra-particlemorphological concentration/density database.

[0058] Specifically, each imaged particle, p_(i), of chemically pureparticulate substance 10 being analyzed is considered morphologicallyheterogeneous, and features a plurality of intra-particle morphologicalregion types, R_(j), for j=1 to J different types of intra-particlemorphological regions identified in, or assigned to, a particle,corresponding to the intra-particle region group sub-set identifier,R_(j), used in Step 3 for distinguishing among the plurality of sub-setsof intra-particle spectral fingerprint pattern data, FP(p_(i) R_(j)),associated with the same set of single-particle spectral fingerprintdata, F(p_(i)).

[0059] Each intra-particle morphological region type, R_(j), isassociated with a surface concentration value, SC(R_(j)), and a densityvalue, D(R_(j)), of the chemically pure substance making up each imagedparticle, p_(i), where SC(R_(j)), and D(R_(j)) vary throughout eachimaged particle, p_(i). Due to this local, intra-particle, variation orheterogeneity in particle morphology such as shape or geometry andporosity, and, due to local, intra-particle, variation or heterogeneityin surface concentration and/or density of the chemically pure substanceof imaged particle, p_(i), incident energy 16 is affected differently byeach intra-particle morphological region type, R_(j). Thisphysicochemical phenomenon during imaging particles of chemically pureparticulate substance 10, enables forming intra-particle region group,RG(p_(i)), in Step 3, featuring the plurality of sub-sets ofintra-particle spectral fingerprint pattern data, FP(p_(i) R_(j)), whereselected data elements in each sub-set, FP(p_(i), R_(j)), are shiftedrelative to corresponding data elements in each remaining sub-set,FP(p_(i), R_(k)), for k not equal to j, in the same intra-particleregion group, RG(p_(i)).

[0060] Values of SC(R_(j)), and D(R_(j)) are obtained by relating thespectral imaging data, in general, and by relating the focus-fusionmulti-layer spectral imaging data, in particular, in each intra-particleregion group, RG(p_(i)), obtained and stored from imaging the sample ofchemically pure particulate substance, to empirically determinedspectral imaging data in a standard intra-particle region group,RG(p_(i))^(S), obtained and stored from imaging a standard sample of achemically pure particulate substance featuring known local,intra-particle, variation or heterogeneity in particle morphology suchas shape or geometry and porosity, and, known local, intra-particle,variation or heterogeneity in surface concentration and/or density ofthe chemically pure substance of the standard sample.

[0061] Accordingly, for each imaged particle, p_(i), the set ofintra-particle morphological concentration/density data is referred toas MCD[p_(i): R_(j), SC(R_(j)), D(R_(j))], for j=1 to J different typesof intra-particle morphological regions. For example, for imagedparticle p₁, the set of intra-particle morphologicalconcentration/density data is written as: MCD[p₁: R_(j), SC(R_(j)),D(R_(j))], for j=1 to 4. SC(R_(j)) and D(R_(j)), for j=1 to 4, areevaluated from the four sub-sets of intra-particle spectral fingerprintpattern data, FP(p₁, R₁), FP(p₁, R₂), FP(p₁, R₃), and FP(p₁, R₄),respectively, where each sub-set is characterized by the correspondingintra-particle spectral fingerprint pattern spectrum, S(p₁, R₁), S(p₁,R₂), S(p₁, R₃), and S(p₁, R₄), respectively, and associated with fourcorresponding different intra-particle morphological region types, R₁,R₂, R₃, and R₄. Thus, referring to FIG. 3, for imaged particle, p₁, thecomplete set of intra-particle morphological concentration/density databecomes: MCD[p₁: R₁, SC(R₁), D(R₁); R₂, SC(R₂), D(R₂); R₃, SC(R₃),D(R₃); R₄, SC(R₄), D(R₄)], referenced by 40.

[0062] In Step 5, there is generating an intra-particle morphologicalconcentration/density map from each set of intra-particle morphologicalconcentration/density data, for illustrating local, intra-particle,morphological distribution of concentration and density of thechemically pure substance throughout the particle associated with thatset of intra-particle morphological concentration/density data.

[0063] This step is performed for each of a number, n, imaged particlesof the substance, for generating n morphological concentration/densitymaps, relating to the chemically pure particulate substance 10. Eachmorphological concentration/density map is stored in an intra-particlemorphological concentration/density map database.

[0064] Specifically, for each imaged particle, p_(i), of chemically pureparticulate substance 10 being analyzed, there is generating anintra-particle morphological concentration/density map, M[p_(i)], fromeach set of intra-particle morphological concentration/density data,MCD[p_(i): R_(j), SC(R_(j)), D(R_(j))], for j=1 to J, featuring Jdifferent types of intra-particle morphological regions, where eachintra-particle morphological region type, R_(j), is associated with asurface concentration value, SC(R_(j)), and a density value, D(R_(j)),of the chemically pure substance.

[0065] Referring again to FIG. 3, for imaged particle, p₁, having theset of intra-particle morphological concentration/density data, MCD[p₁:R₁, SC(R₁), D(R₁); R₂, SC(R₂), D(R₂); R₃, SC(R₃), D(R₃); R₄, SC(R₄),D(R₄)] 40, formed and assigned values according to previously describedStep 4 above, there is generating intra-particle morphologicalconcentration/density map, M[p₁] 50.

[0066] In Step 6, there is generating a morphologicalconcentration/density histogram, or frequency distribution, from theplurality of sets of the intra-particle morphologicalconcentration/density data, for illustrating a statistically basedglobal morphological distribution of surface concentration and densitythroughout the entire chemically pure particulate sample.

[0067] This step is performed using the previously obtained data sets ofthe number, n, imaged particles of the substance, for generating themorphological concentration/density histogram, relating to andrepresentative of the entire chemically pure particulate substance 10.Each histogram is stored in a morphological concentration/densityhistogram database.

[0068] Specifically, using the previously obtained data sets of the nimaged particles, p_(i), for i=1 to n, making up sample number,(sample)_(h), of chemically pure particulate substance 10 beinganalyzed, there is generating a morphological concentration/densityhistogram, H[(sample)_(h)], from the plurality of sets of intra-particlemorphological concentration/density data, MCD[p_(i): R_(j), SC(R_(j)),D(R_(j))], for i=1 to n, and j=1 to J, for each particle number, i, andfor J different types of intra-particle morphological regions, where Jcan vary among the imaged particles.

[0069] For example, referring to FIG. 4, a schematic diagramillustrating a morphological concentration/density histogram generatedfrom a plurality of sets of intra-particle morphologicalconcentration/density map data, from the data sets of the n imagedparticles of (sample)₁ representative of substance 10, morphologicalconcentration/density histogram, H[(sample)₁] 60, is generated from theplurality of sets of intra-particle morphological concentration/densitydata, MCD[p_(i): R_(j), SC(R_(j)), D(R_(j))], for i=1 to n, and j=1 toJ, for each particle number, i, corresponding to a statisticalmorphological distribution of a plurality of individual particles ofchemically pure particulate substance 10. Morphologicalconcentration/density histogram, H[(sample)₁] 60, features a graphicalplot of the statistical distribution of the surface concentration,SC(R_(j)), of the chemically pure substance in each intra-particlemorphological region type, R_(j), as a function of particle diameter(microns), among the plurality of particles of substance 10. Forillustrative purposes, four intra-particle morphological region types,R₁, R₂, R₃, and R₄, each with a corresponding intra-particle surfaceconcentration, SC(R₁), SC(R₂), SC(R₃), and SC(R₄), respectively, areshown in morphological concentration/density histogram, H[(sample)₁] 60.

[0070] While the invention has been described in conjunction withspecific embodiments thereof, it is evident that many alternatives,modifications and variations will be apparent to those skilled in theart. Accordingly, it is intended to embrace all such alternatives,modifications and variations that fall within the spirit and broad scopeof the appended claims.

What is claimed is:
 1. A method for generating intra-particlemorphological concentration/density maps and histograms of a chemicallypure particulate substance, comprising the steps of: (a) acquiring a setof spectral images by a spectral imaging system for each of a number ofparticles of the chemically pure particulate substance having aplurality of said particles; (b) performing pattern recognitionclassification analysis on each said set of said acquired spectralimages for each said imaged particle, for forming a number of sets ofsingle-particle spectral fingerprint data; (c) identifying at least onespectral shift in each said set of single-particle spectral fingerprintdata associated with each said imaged particle, for forming anintra-particle region group featuring a plurality of sub-sets ofintra-particle spectral fingerprint pattern data, where selected dataelements in each said sub-set are shifted relative to corresponding saiddata elements in each remaining said sub-set in same said intra-particleregion group; (d) forming a set of intra-particle morphologicalconcentration/density data relating to each said imaged particle fromeach said intra-particle region group; (e) generating each of theintra-particle morphological concentration/density maps from each saidset of said intra-particle morphological concentration/density data; and(f) generating each of the morphological concentration/densityhistograms from a plurality of said sets of said intra-particlemorphological concentration/density data, for illustrating astatistically based global morphological distribution of surfaceconcentration and density throughout the chemically pure particulatesubstance.
 2. The method of claim 1, wherein the chemically pureparticulate substance features at least one chemically pure compound. 3.The method of claim 1, wherein the chemically pure particulate substanceis selected from the group consisting of a powder, a powder mixture, amedicinal powder featuring at least one active ingredient and at leastone inactive ingredient, a frozen suspension of a powder, and abiological specimen.
 4. The method of claim 1, wherein the chemicallypure particulate substance features intra-particle heterogeneousmorphology and regions of varying concentration and density.
 5. Themethod of claim 1, wherein physicochemical properties andcharacteristics of said particles are selected from the group consistingof independent of particle depth and dependent of particle depth.
 6. Themethod of claim 1, wherein step (a) said spectral images arefocus-fusion multi-layer spectral images acquired by focus-fusionmulti-layer spectral imaging of said particles of the chemically pureparticulate substance.
 7. The method of claim 1, wherein step (a) saidspectral imaging system includes an imaging energy source supplyingimaging source energy incident upon the chemically pure particulatesubstance, said imaging source energy is affected by said imagedparticles by at least one mechanism selected from the group consistingof absorption, reflection, transmission, diffraction, scattering,fluorescence, and phosphorescence.
 8. The method of claim 1, wherebyeach said set of single-particle spectral fingerprint data ischaracterized by a single-particle spectral fingerprint spectrumfeaturing intensity or amplitude plotted as a function of incidentimaging energy affected by a said imaged particle and collected duringimaging said particle by said spectral imaging system.
 9. The method ofclaim 8, whereby said affected energy is expressed in a term selectedfrom the group consisting of wavelength, frequency, and, wavenumber, ofelectromagnetic radiation emitted by said imaged particle.
 10. Themethod of claim 1, wherein step (c) said identifying said at least onespectral shift is performed for each said imaged particle of thechemically pure substance, for forming a plurality of saidintra-particle region groups of said sub-sets of said intra-particlespectral fingerprint pattern data relating to the entire chemically pureparticulate substance.
 11. The method of claim 1, wherein step (c) saidselected data elements of said sub-sets of said intra-particle spectralfingerprint pattern data are selected from the group consisting ofincident imaging energy affected by a said imaged particle and amplitudeof said incident imaging energy affected by said imaged particle. 12.The method of claim 1, wherein step (c) said selected data elements ofsaid sub-sets of said intra-particle spectral fingerprint pattern dataare incident imaging energy affected by a said imaged particle.
 13. Themethod of claim 1, wherein step (c) each said sub-set of saidintra-particle spectral fingerprint pattern data is characterized by anintra-particle spectral fingerprint pattern spectrum featuring intensityor amplitude plotted as a function of incident imaging energy affectedby a said imaged particle.
 14. The method of claim 1, whereby for eachsaid imaged particle, said set of said intra-particle morphologicalconcentration/density data features a plurality of intra-particlemorphological region types, where each said intra-particle morphologicalregion type is associated with a different value of said surfaceconcentration and a different value of said density of the chemicallypure particulate substance.
 15. A method for identifying intra-particlemorphological distribution of surface concentration and density of achemically pure particulate substance, comprising the steps of: (a)acquiring a set of spectral images by a spectral imaging system for eachof a number of particles of the chemically pure particulate substancehaving a plurality of said particles; (b) performing pattern recognitionclassification analysis on each said set of said acquired spectralimages for each said imaged particle, for forming a number of sets ofsingle-particle spectral fingerprint data; (c) identifying at least onespectral shift in each said set of single-particle spectral fingerprintdata associated with each said imaged particle, for forming anintra-particle region group featuring a plurality of sub-sets ofintra-particle spectral fingerprint pattern data, where selected dataelements in each said sub-set are shifted relative to corresponding saiddata elements in each remaining said sub-set in same said intra-particleregion group; (d) forming a set of intra-particle morphologicalconcentration/density data relating to each said imaged particle fromeach said intra-particle region group; and (e) forming a plurality ofintra-particle morphological region types from each said set of saidintra-particle morphological concentration/density data, where each saidintra-particle morphological region type is associated with a differentvalue of the surface concentration and a different value of the densityof the chemically pure particulate substance, thereby identifying theintra-particle morphological distribution of the surface concentrationand density of the chemically pure particulate substance.
 16. The methodof claim 15, wherein the chemically pure particulate substance featuresat least one chemically pure compound.
 17. The method of claim 15,wherein the chemically pure particulate substance is selected from thegroup consisting of a powder, a powder mixture, a medicinal powderfeaturing at least one active ingredient and at least one inactiveingredient, a frozen suspension of a powder, and a biological specimen.18. The method of claim 15, wherein the chemically pure particulatesubstance features intra-particle heterogeneous morphology and regionsof varying concentration and density.
 19. The method of claim 15,wherein physicochemical properties and characteristics of said particlesare selected from the group consisting of independent of particle depthand dependent of particle depth.
 20. The method of claim 15, whereinstep (a) said spectral images are focus-fusion multi-layer spectralimages acquired by focus-fusion multi-layer spectral imaging of saidparticles of the chemically pure particulate substance.
 21. The methodof claim 15, wherein step (a) said spectral imaging system includes animaging energy source supplying imaging source energy incident upon thechemically pure particulate substance, said imaging source energy isaffected by said imaged particles by at least one mechanism selectedfrom the group consisting of absorption, reflection, transmission,diffraction, scattering, fluorescence, and phosphorescence.
 22. Themethod of claim 15, whereby each said set of single-particle spectralfingerprint data is characterized by a single-particle spectralfingerprint spectrum featuring intensity or amplitude plotted as afunction of incident imaging energy affected by a said imaged particleand collected during imaging said particle by said spectral imagingsystem.
 23. The method of claim 22, whereby said affected energy isexpressed in a term selected from the group consisting of wavelength,frequency, and, wavenumber, of electromagnetic radiation emitted by saidimaged particle.
 24. The method of claim 15, wherein step (c) saididentifying said at least one spectral shift is performed for each saidimaged particle of the chemically pure substance, for forming aplurality of said intra-particle region groups of said sub-sets of saidintra-particle spectral fingerprint pattern data relating to the entirechemically pure particulate substance.
 25. The method of claim 15,wherein step (c) said selected data elements of said sub-sets of saidintra-particle spectral fingerprint pattern data are selected from thegroup consisting of incident imaging energy affected by a said imagedparticle and amplitude of said incident imaging energy affected by saidimaged particle.
 26. The method of claim 15, wherein step (c) saidselected data elements of said sub-sets of said intra-particle spectralfingerprint pattern data are incident imaging energy affected by a saidimaged particle.
 27. The method of claim 15, wherein step (c) each saidsub-set of said intra-particle spectral fingerprint pattern data ischaracterized by an intra-particle spectral fingerprint pattern spectrumfeaturing intensity or amplitude plotted as a function of incidentimaging energy affected by a said imaged particle.